{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T13:19:53Z","timestamp":1753881593192,"version":"3.41.2"},"reference-count":37,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,1,7]],"date-time":"2021-01-07T00:00:00Z","timestamp":1609977600000},"content-version":"vor","delay-in-days":6,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61572225","61472049"],"award-info":[{"award-number":["61572225","61472049"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>To better reflect the precise clustering results of the data samples with different shapes and densities for affinity propagation clustering algorithm (AP), an improved integrated clustering learning strategy based on three\u2010stage affinity propagation algorithm with density peak optimization theory (DPKT\u2010AP) was proposed in this paper. DPKT\u2010AP combined the ideology of integrated clustering with the AP algorithm, by introducing the density peak theory and k\u2010means algorithm to carry on the three\u2010stage clustering process. In the first stage, the clustering center point was selected by density peak clustering. Because the clustering center was surrounded by the nearest neighbor point with lower local density and had a relatively large distance from other points with higher density, it could help the k\u2010means algorithm in the second stage avoiding the local optimal situation. In the second stage, the k\u2010means algorithm was used to cluster the data samples to form several relatively small spherical subgroups, and each of subgroups had a local density maximum point, which is called the center point of the subgroup. In the third stage, DPKT\u2010AP used the AP algorithm to merge and cluster the spherical subgroups. Experiments on UCI data sets and synthetic data sets showed that DPKT\u2010AP improved the clustering performance and accuracy for the algorithm.<\/jats:p>","DOI":"10.1155\/2021\/6666619","type":"journal-article","created":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T03:08:47Z","timestamp":1610075327000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["An Improved Integrated Clustering Learning Strategy Based on Three\u2010Stage Affinity Propagation Algorithm with Density Peak Optimization Theory"],"prefix":"10.1155","volume":"2021","author":[{"given":"Limin","family":"Wang","sequence":"first","affiliation":[]},{"given":"Wenjing","family":"Sun","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6213-5600","authenticated-orcid":false,"given":"Xuming","family":"Han","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9215-2874","authenticated-orcid":false,"given":"Zhiyuan","family":"Hao","sequence":"additional","affiliation":[]},{"given":"Ruihong","family":"Zhou","sequence":"additional","affiliation":[]},{"given":"Jinglin","family":"Yu","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7596-407X","authenticated-orcid":false,"given":"Milan","family":"Parmar","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,1,7]]},"reference":[{"key":"e_1_2_11_1_2","doi-asserted-by":"publisher","DOI":"10.24818\/18423264\/54.1.20.11"},{"key":"e_1_2_11_2_2","doi-asserted-by":"publisher","DOI":"10.24818\/18423264\/53.2.19.05"},{"key":"e_1_2_11_3_2","first-page":"93","article-title":"Developing an index score for the internal auditor profile in Romania based on real data analysis","volume":"53","author":"Miheala M.","year":"2019","journal-title":"Economic Computation and Economic Cybernetics Studies and Research"},{"key":"e_1_2_11_4_2","doi-asserted-by":"publisher","DOI":"10.33168\/JSMS.2020.0203"},{"key":"e_1_2_11_5_2","doi-asserted-by":"publisher","DOI":"10.7717\/peerj.3035"},{"key":"e_1_2_11_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSE.2018.2842113"},{"key":"e_1_2_11_7_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10044-019-00785-4"},{"key":"e_1_2_11_8_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0209368"},{"key":"e_1_2_11_9_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-014-1671-4"},{"key":"e_1_2_11_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/lsp.2017.2674960"},{"key":"e_1_2_11_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.07.027"},{"key":"e_1_2_11_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2018.02.007"},{"key":"e_1_2_11_13_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-018-1320-1"},{"key":"e_1_2_11_14_2","doi-asserted-by":"publisher","DOI":"10.1097\/ju.0000000000000354"},{"key":"e_1_2_11_15_2","doi-asserted-by":"publisher","DOI":"10.1109\/LGRS.2012.2233711"},{"key":"e_1_2_11_16_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2956963"},{"key":"e_1_2_11_17_2","doi-asserted-by":"publisher","DOI":"10.17559\/TV-20150314115623"},{"key":"e_1_2_11_18_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0198948"},{"key":"e_1_2_11_19_2","doi-asserted-by":"publisher","DOI":"10.17559\/TV-20171121052315"},{"key":"e_1_2_11_20_2","first-page":"1125","article-title":"Gravity theory-based affinity propagation clustering algorithm and its applications","volume":"25","author":"Wang L.","year":"2018","journal-title":"Tehnicki Vjesnik-Technical Gazette"},{"key":"e_1_2_11_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.energy.2019.05.042"},{"key":"e_1_2_11_22_2","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/8509142"},{"key":"e_1_2_11_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.10.022"},{"key":"e_1_2_11_24_2","doi-asserted-by":"publisher","DOI":"10.1049\/iet-sen.2016.0261"},{"key":"e_1_2_11_25_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1242072"},{"key":"e_1_2_11_26_2","doi-asserted-by":"publisher","DOI":"10.1126\/science.1136800"},{"key":"e_1_2_11_27_2","first-page":"45","article-title":"Algorithm of three-party combined judgment analysis engine for earthquake early warning system","volume":"9","author":"Park Y. 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